Preimplantation genetic testing (PGT) of in-vitro-fertilized embryos has been proposed as a method to reduce transmission of common disease; however, more comprehensive embryo genetic assessment, combining the effects of common variants and rare variants, remains unavailable. Here, we used a combination of molecular and statistical techniques to reliably infer inherited genome sequence in 110 embryos and model susceptibility across 12 common conditions. We observed a genotype accuracy of 99.0–99.4% at sites relevant to polygenic risk scoring in cases from day-5 embryo biopsies and 97.2–99.1% in cases from day-3 embryo biopsies. Combining rare variants with polygenic risk score (PRS) magnifies predicted differences across sibling embryos. For example, in a couple with a pathogenic BRCA1 variant, we predicted a 15-fold difference in odds ratio (OR) across siblings when combining versus a 4.5-fold or 3-fold difference with BRCA1 or PRS alone. Our findings may inform the discussion of utility and implementation of genome-based PGT in clinical practice.
In this clinical validation study, we developed and validated a urinary Q-Score generated from the quantitative test QSant, formerly known as QiSant, for the detection of biopsy-confirmed acute rejection in kidney transplants. Using a cohort of 223 distinct urine samples collected from three independent sites and from both adult and pediatric renal transplant patients, we examined the diagnostic utility of the urinary Q-Score for detection of acute rejection in renal allografts. Statistical models based upon the measurements of the six QSant biomarkers (cell-free DNA, methylated-cell-free DNA, clusterin, CXCL10, creatinine, and total protein) generated a renal transplant Q-Score that reliably differentiated stable allografts from acute rejections in both adult and pediatric renal transplant patients. The composite Q-Score was able to detect both T cell-mediated rejection and antibody-mediated rejection patients and differentiate them from stable non-rejecting patients with a receiver–operator characteristic curve area under the curve of 99.8% and an accuracy of 98.2%. Q-Scores < 32 indicated the absence of active rejection and Q-Scores ≥ 32 indicated an increased risk of active rejection. At the Q-Score cutoff of 32, the overall sensitivity was 95.8% and specificity was 99.3%. At a prevalence of 25%, positive and negative predictive values for active rejection were 98.0% and 98.6%, respectively. The Q-Score also detected subclinical rejection in patients without an elevated serum creatinine level but identified by a protocol biopsy. This study confirms that QSant is an accurate and quantitative measurement suitable for routine monitoring of renal allograft status.
Background Diagnosis of rare genetic diseases can be a long, expensive and complex process, involving an array of tests in the hope of obtaining an actionable result. Long-read sequencing platforms offer the opportunity to make definitive molecular diagnoses using a single assay capable of detecting variants, characterizing methylation patterns, resolving complex rearrangements, and assigning findings to long-range haplotypes. Here, we demonstrate the clinical utility of Nanopore long-read sequencing by validating a confirmatory test for copy number variants (CNVs) in neurodevelopmental disorders and illustrate the broader applications of this platform to assess genomic features with significant clinical implications. Methods We used adaptive sampling on the Oxford Nanopore platform to sequence 25 genomic DNA samples and 5 blood samples collected from patients with known or false-positive copy number changes originally detected using short-read sequencing. Across the 30 samples (a total of 50 with replicates), we assayed 35 known unique CNVs (a total of 55 with replicates) and one false-positive CNV, ranging in size from 40 kb to 155 Mb, and assessed the presence or absence of suspected CNVs using normalized read depth. Results Across 50 samples (including replicates) sequenced on individual MinION flow cells, we achieved an average on-target mean depth of 9.5X and an average on-target read length of 4805 bp. Using a custom read depth-based analysis, we successfully confirmed the presence of all 55 known CNVs (including replicates) and the absence of one false-positive CNV. Using the same CNV-targeted data, we compared genotypes of single nucleotide variant loci to verify that no sample mix-ups occurred between assays. For one case, we also used methylation detection and phasing to investigate the parental origin of a 15q11.2-q13 duplication with implications for clinical prognosis. Conclusions We present an assay that efficiently targets genomic regions to confirm clinically relevant CNVs with a concordance rate of 100%. Furthermore, we demonstrate how integration of genotype, methylation, and phasing data from the Nanopore sequencing platform can potentially simplify and shorten the diagnostic odyssey.
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